{Please note: an additional fee is assessed for this session. See the registration form.}

Learning Goals (Abstract): Attendees will learn the key concepts of metadata creation and use that are compatible with the creation of linked data. They will get a basic introduction to the Semantic Web and the concept of "linked data," including the use of identifiers, the creation of statements and graphs, and an introduction to ontologies and vocabularies. The seminar includes hands-on exercises where attendees learn concepts by creating simple metadata using Semantic Web concepts. There is an emphasis on linked data as created by libraries, but data from other communities is included. No programming expertise is required.

Who Should Attend: This seminar is appropriate for metadata creators who are currently creating traditional record-based metadata (include library catalogers) as well as information technology professionals who are beginning to work with linked data.

Summary Outline:

Part I: Metadata Basics

Data with a purpose
Understanding data
Identifiers and identities
Making a statement & creating graphs

Part II: Linked Data and the Semantic Web

Introduction to the Semantic Web
The Uniform Resource Identifier
Defining and using ontologies
Defining and using controlled vocabularies

Tuesday 4th September 2012

{Please note: an additional fee is assessed for this session. See the registration form.}

Learning Goals (Abstract): This tutorial session will focus on application profile and ontology design for semantic interoperability. The participants will learn:

how to design application profiles using Oxygen XML editor;
how to design RDF/OWL ontology using Protégé ontology editor; and
how to design Topic Map ontology using Ontopoly topic maps editor.

Who Should Attend: This tutorial can be beneficial for those who want to learn about metadata and ontology in general with some technical depth, are interested in providing better information service by utilizing metadata and ontology, and want to acquire in technical knowledge of how to develop application profiles and ontologies.

Keynote Abstract: Preferences are ubiquitous in everyday decision making. They should therefore be an essential ingredient in every reasoning tool. Preferences are often used in collective decision making, where each agent expresses its preferences over a set of possible decisions, and a chair aggregates such preferences to come out with the "winning" decision. Indeed, preference reasoning and multi-agent preference aggregations are areas of growing interest within artificial intelligence.

Preferences have classically been the subject also of social choice studies, in particular those related to elections and voting theory. In this context, several voters express their preferences over the candidates and a voting rule is used to elect the winning candidate. Economists, political theorist, mathematicians, as well as philosophers, have made tremendous efforts to study this scenario and have obtained many theoretical results about the properties of the voting rules that one can use.

Since, after all, this scenario is not so different from multi-agent decision making, it is not surprising that in recent years the area of multi-agent systems has been invaded by interesting papers trying to adapt social choice results to multi-agent setting. An adaptation is indeed necessary, since, besides the apparent similarity, there are many issues in multi-agent settings that do not occur in a social choice context: a large set of candidates with a combinatorial structure, several formalisms to model preferences compactly, preference orderings including indifference and incomparability, uncertainty, as well as computational concerns.

The above considerations are the basis of a relatively new research area called computational social choice, which studies how social choice and AI can fruitfully cooperate to give innovative and improved solutions to aggregating preferences given by multiple agents. This talk will present this interdisciplinary area of research and will describe several recent results regarding some of the issues mentioned above, with special focus on robustness of multi-agent preference aggregation with respect to influences, manipulation, and bribery.

Bio-data: Francesca Rossi is a full professor of computer science at the University of Padova, Italy. Her research interests include constraint reasoning, preference modelling and aggregation, multi-agent systems, and computational social choice. She has been president of the international association for constraint programming (ACP) from 2003 to 2007, she is an IJCAI trustee since 2009 and an ECCAI fellow since 2008. She has been program chair of CP 2003 and she will be program chair of IJCAI 2013. She is a member of the advisory board of JAIR, a column editor for the Journal of Logic and Computation, and a member of the editorial board of Constraints, Artificial Intelligence, JAIR, AMAI, and KAIS. She has published more than 130 papers and one book. She co-edited 16 volumes, between special issues, conference proceedings, and the handbook of constraint programming.

Dan Brickley is best known for his work on Web standards in the W3C community, where he helped create the Semantic Web project and many of its defining technologies. Dan is currently working with Google on outreach activities related to the Schema.org initiative. Previous work included six years on the W3C technical staff, establishing ILRT's Semantic Web group at the University of Bristol, and more recently at Joost, an Internet TV start-up, and at the Vrije University Amsterdam. He has been involved with resource discovery metadata since 1994 when he published the first HTML Philosophy guide on the Web, and has been exploring distributed, collaborative approaches to "finding stuff" ever since.

Keynote Abstract: The original 1995 Dublin Core vision of simple, publisher-provided metadata records for Web pages has finally entered the mainstream. From its earliest days, the Dublin Core community was positioned somewhere between the world of search, and the world of the library. The RDF-based approaches long championed by DCMI have recently enjoyed high profile adoption amongst both search engines and libraries. Where does this leave the Dublin Core as a community? Do we settle down into a quiet life of long-term metadata vocabulary maintenance, or are there larger challenges that emerge from this landscape of newly linked, networked information? Dan Brickley will revisit the history of the Dublin Core, outline the state of the art for bibliographic and Web metadata, and outline possible new roles, information-linking problems and practical opportunities for the Dublin Core as a project and as a growing community.

Thursday 6th September 2012

Keynote Abstract: The games agents play--in markets, conflicts, or most other contexts--often defy strict game-theoretic analysis. Games may be unmanageably large (combinatorial or infinite state or action spaces), and present severely imperfect information, which could be further complicated by partial dynamic revelation. Moreover, the game may be specified procedurally, for instance by a simulator, rather than in an explicit game form. With colleagues and students over the past few years, I have been developing a body of techniques for strategic analysis, adopting the game-theoretic framework but employing it in domains where direct "model-and-solve" cannot apply. This empirical game-theoretic methodology embraces simulation, approximation, statistics and learning, and search. Through applications to canonical auction games, and other rich multiagent scenarios, we demonstrate the value of empirical methods for extending the scope of game-theoretic analysis.

Bio-data: Michael P. Wellman is Professor of Computer Science & Engineering at the University of Michigan, where he leads the Strategic Reasoning Group in the Artificial Intelligence Laboratory. He received a PhD from the Massachusetts Institute of Technology in 1988 for his work in qualitative probabilistic reasoning and decision-theoretic planning. For over twenty years, Wellman has worked at the intersection of Computer Science and Economics, in the process pioneering approaches to computational markets and trading agent design and analysis. Market designs and infrastructure developed by his research group have been influential in the academic community as well as in electronic commerce practice. Wellman is a Fellow of the Association for Computing Machinery, and the Association for the Advancement of Artificial Intelligence.

Keynote Abstract: When humans communicate with each other, they do not just exchange information in an explicit manner. In addition, a myriad of implicit social signals is conveyed that may even have a deeper influence on the success of a conversation than the word meanings themselves. Due to limitations in input processing technology, human-agent interactions still suffer from an asymmetry in communication channels. While embodied conversational agents employ a large variety of communication signals to converse with human users, social signals elicited by the human interlocutor are often ignored. As a consequence, human-agent interactions still remain a rather unnatural experience. In the worst case, the disregard of social signals may even lead to serious misconceptions. In my talk I will show how recent advances in the area of social signal processing can contribute to more empathetic human-agent interactions in which agents appear sensitive and attentive towards the human interlocutor. In addition, I will demonstrate the potential of social signal processing technology as a tool to evaluate the quality of human-agent interactions. The talk will be illustrated by examples from human interaction with virtual agents and robots.

Bio-data: Elisabeth André is full professor of Computer Science at Augsburg University and Chair of the Research Unit for Human-Centered Multimedia. Prior to that, she worked as a principal researcher at DFKI GmbH where she has been leading various academic and industrial projects in the area of intelligent user interfaces. Elisabeth André holds a long track record in embodied conversational agents, multimodal interfaces and social signal processing. Elisabeth André is on the editorial board of various renowned international journals, such as Journal of Autonomous Agents and Multi-Agent Systems (JAAMAS), IEEE Transactions on Affective Computing (TAC), ACM Transactions on Intelligent Interactive Systems (TIIS), and AI Communications. In summer 2007 Elisabeth André was nominated Fellow of the Alcatel-Lucent Foundation for Communications Research. In 2010, she was elected a member of the prestigious German Academy of Sciences Leopoldina, the Academy of Europe and AcademiaNet.

Friday 7th September 2012

Karen Coyle is a librarian with over thirty years of experience with library technology. She now consults in a variety of areas relating to digital libraries. Karen has published dozens of articles and reports, most available on her web site, kcoyle.net. She has served on standards committees including the MARC standards group (MARBI), the OpenURL standard, and was an ALA representative to the e-book standards development that led to ePub. She follows, writes, and speaks on a wide range policy areas, including intellectual property, privacy, and public access to information. As a consultant she works primarily on metadata development and technology planning. She is currently investigating the possibilities offered by the Semantic Web and Linked Data technology.

Keynote Abstract: Much of the activity today in the creation of Resource Description Framework (RDF) ontologies and the building of actual linked data is based on sets of data that were created for technologies that pre-date the Semantic Web. Although it is possible to transform, for example, the data in a relational database to RDF, we must assume that such data may not represent "linked data thinking". Karen Coyle will talk about "thinking differently" about data with examples from libraries and other communities with substantial reservoirs of legacy data.

» Joachim Neubert, German National Library of Economics, Germany
» Johannes Keizer, Food and Agriculture Organization of the United Nations (FAO), Italy
» John Fereira, Cornell University Library, United States
» Thomas Baker, Dublin Core Metadata Initiative (DCMI), United States

A number of the organizations likely to be represented at the DC-2012 use a Drupal platform (e.g., FAO and VIVO) or are planning such a migration (ZBW Labs and DCMI). This special session would explore the relationship between Drupal and Linked Open Data (LOD) vocabularies—specifically, how Drupal systems can ingest and use LOD vocabularies and publish data using LOD vocabularies. How does, or how might, Drupal interact with the Agrovoc Vocbench, AgInfra tools, metadata registries, or Schema.org?

Ingesting and displaying Linked Open Data from SPARQL endpoints using Drupal extensions such as views, sparql_views, and rdfx (e.g., see Lin Clark's video, linked below).

"Web Taxonomy", a Drupal module for integrating excerpts of terminologies from the LOD cloud as taxonomies for referencing in Drupal RDFa. It has been suggested that Agrovoc, with its large set of supported languages, might use the Web Taxonomy module to index in one language, then automatically update and display labels in all supported languages.

"Economics Taxonomies", a Drupal plugin under development by ZBW Labs, which leverages JSON responses from external autosuggest Web services and SPARQL endpoints.

"Neologism", a Drupal module from DERI, which pushes vocabularies into the LOD cloud.

"AgrovocField", a Drupal module that connects to the Agrovoc web services built on the VocBench and provides a user-friendly widget with an autocomplete box. In future, will support automatically tagging a node field (textarea, file attachment or web URL) using the Agrotagger web +services based on Agrovoc.

"Autotagging" and "Textmining_API", early-beta Drupal modules that support using 3rd party services for automatic indexing and are designed to be extensible by plugging in other services.

"Schemaorg", a Drupal 7 module.

"schemaorg_kickstarter", a Drupal 7 distribution that already includes content types with typical mappings to schema.org classes and properties.

The session would begin with lightning talks about projects that use or are implementing any of the approaches above. These presentations would lead into "unconference"-style brainstorming to identify opportunities for sharing expertise, pooling efforts, or defining joint goals.

Keynote Abstract: Systems biology is an attempt to understand biological system as system thereby triggering innovations in medical practice, drug discovery, bio-engineering, and global sustainability problems. The fundamental difficulties lies in the complexity of biological systems that have evolved through billions of years. Nevertheless, there are fundamental principles governing biological systems as complex evolvable systems that has been optimized for certain environmental constraints. Broad range of AI technologies can be applied for systems biology such as text-mining, qualitative physics, marker-passing algorithms, statistical inference, machine learning, etc. In fact, systems biology is one of the best field that AI technologies can be best applied to make high impact research that can impact real-world. This talk addresses basic issues in systems biology, especially in systems drug discovery and coral reef systems biology, and discusses how AI can contribute to make difference.

Bio-data: Hiroaki Kitano received B.A. in physics from International Christian University, Tokyo, and Ph.D. in computer science from Kyoto University. From 1988 to 1994, he was a visiting researcher at Center for Machine Translation at Carnegie Mellon University. His research career includes Project Director of Kitano Symbiotic Systems Project, ERATO, Japan Science and Technology Corporation (1998-2003) followed by Project Director of Kitano Symbiotic Systems Project, ERATO-SORST, Japan Science and Technology Agency (2003-2008), visiting professor of the University of Tokyo, and so on. He is also visiting professor of Keio University, Director of Division of Cancer Systems Biology, Cancer Institute, Japanese Foundation for Cancer Research, Scientific Advisor of Pfizer Inc. (Insulin Resistance Program), Special Professor of University of Amsterdam, Guest professor of Linköping University, Sweden, Founding President of The RoboCup Federation and Trustee of IJCAI(2005- 2015). He served on President, Board of Trustees of IJCAI from 2009 to 2011 as well as Conference Chair of IJCAI-09. He received The Computers and Thought Award from the International Joint Conferences on Artificial Intelligence in 1993, Prix Ars Electronica 2000, Design Award 2001 from Japan Inter-Design Forum, Good Design Award 2001 and Nature's 2009 Japan Mid-career Award for Creative Mentoring in Science, as well as being an invited artist for Biennale di Venezia 2000 and Museum of Modern Art (MoMA) New York in 2001. His research interests include AI, Robotics, and Systems Biology.